Abstract
Protein kinases (PKs) are key components of protein phosphorylation based signaling networks in eukaryotic cells. They have been identified as being implicated in many diseases. High-resolution X-ray crystallographic data exist for many PKs and, in many cases, these structures are co-complexed with inhibitors. Although this valuable information confirms the precise structure of PKs and their complexes, it ignores the dynamic movements of the structures which are relevant to explain the affinities and selectivity of the ligands, to characterize the thermodynamics of the solvated complexes, and to derive predictive models. Atomistic molecular dynamics (MD) simulations present a convenient way to study PK-inhibitor complexes and have been increasingly used in recent years in structure-based drug design. MD is a very useful computational method and a great counterpart for experimentalists, which helps them to derive important additional molecular information. That enables them to follow and understand structure and dynamics of protein-ligand systems with extreme molecular detail on scales where motion of individual atoms can be tracked. MD can be used to sample dynamic molecular processes, and can be complemented with more advanced computational methods (e.g., free energy calculations, structure-activity relationship analysis). This review focuses on the most commonly applications to study PK-inhibitor complexes using MD simulations. Our aim is that researchers working in the design of PK inhibitors be aware of the benefits of this powerful tool in the design of potent and selective PK inhibitors.
Keywords: Molecular dynamics, protein kinases, docking, free energy calculations, 4D-QSAR, protein phosphorylation, X-ray crystallographic data, PK inhibitors, threonine residues, signal proteins
Current Pharmaceutical Design
Title:Molecular Dynamics of Protein Kinase-Inhibitor Complexes: A Valid Structural Information
Volume: 18 Issue: 20
Author(s): Julio Caballero and Jans H. Alzate-Morales
Affiliation:
Keywords: Molecular dynamics, protein kinases, docking, free energy calculations, 4D-QSAR, protein phosphorylation, X-ray crystallographic data, PK inhibitors, threonine residues, signal proteins
Abstract: Protein kinases (PKs) are key components of protein phosphorylation based signaling networks in eukaryotic cells. They have been identified as being implicated in many diseases. High-resolution X-ray crystallographic data exist for many PKs and, in many cases, these structures are co-complexed with inhibitors. Although this valuable information confirms the precise structure of PKs and their complexes, it ignores the dynamic movements of the structures which are relevant to explain the affinities and selectivity of the ligands, to characterize the thermodynamics of the solvated complexes, and to derive predictive models. Atomistic molecular dynamics (MD) simulations present a convenient way to study PK-inhibitor complexes and have been increasingly used in recent years in structure-based drug design. MD is a very useful computational method and a great counterpart for experimentalists, which helps them to derive important additional molecular information. That enables them to follow and understand structure and dynamics of protein-ligand systems with extreme molecular detail on scales where motion of individual atoms can be tracked. MD can be used to sample dynamic molecular processes, and can be complemented with more advanced computational methods (e.g., free energy calculations, structure-activity relationship analysis). This review focuses on the most commonly applications to study PK-inhibitor complexes using MD simulations. Our aim is that researchers working in the design of PK inhibitors be aware of the benefits of this powerful tool in the design of potent and selective PK inhibitors.
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Cite this article as:
Caballero Julio and H. Alzate-Morales Jans, Molecular Dynamics of Protein Kinase-Inhibitor Complexes: A Valid Structural Information, Current Pharmaceutical Design 2012; 18 (20) . https://dx.doi.org/10.2174/138161212800672705
DOI https://dx.doi.org/10.2174/138161212800672705 |
Print ISSN 1381-6128 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4286 |
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